In general, a receiver in a wireless communication system does not have a priori knowledge of the physical channel over which the transmitted signal propagates or the time at which a transmitter transmits the signal. Timing synchronization or acquisition, also known as clock recovery, is the process by which a receiver processes a received signal to determine the precise transition points within the received waveform. In other words, the receiver attempts to “synchronize” or align its clock with the clock of the receiving waveform. This process requires the receiver to estimate or otherwise determine the appropriate “timing offset” of the received signal, i.e., the amount of skew between the transmitter's clock and that of the arriving waveform.
Incorrect determination of the timing offset can have detrimental effects on the other receiver operations, such as channel estimation, symbol detection, and the like. For example, an incorrect timing offset may cause the received waveform to be sampled at times during which the waveform is in transition between two symbols resulting in an increased number of symbol detection errors. Thus, synchronization plays a critical role in ensuring reliable communications.
For example, in narrowband (NB) transmissions over additive white Gaussian noise (AWGN) channels, timing synchronization typically comprises “peak-picking” the correlation of the transmit-filter with its template formed at the receiver using a maximum likelihood (ML) or lower complexity sub-optimal, e.g., early-late gate, process. In wideband (WB) transmissions over frequency-selective channels which induce inter-symbol interference (ISI), timing acquisition can become more challenging, particularly in multiple access links which also experience multiuser interference (MUI). However, timing acquisition can be challenging with ISI even in single-user wireless links because the receiver-template must also account for the unknown multipath channel during the synchronization phase.
For this reason, data-aided algorithms relying on training symbols as well as non-data aided, i.e., blind or decision-directed, synchronizers attempt to jointly estimate the timing offset with the discrete-time baseband equivalent ISI channel. Furthermore, data-aided algorithms are bandwidth consuming and interrupt information transmission for training purposes while non-data aided synchronizers require relatively long data records to reliably estimate the statistics, such as sample cyclic correlations, used to estimate the timing offset.
Timing synchronization challenges are magnified in ultra-wideband (UWB) transmissions because the information-bearing waveforms are impulse-like and have lower power, which increases the difficulty in achieving accurate and efficient timing synchronization. Specifically, when ISI effects are particularly pronounced, the bit error rate (BER) may degrade severely due to mistiming and capacity may diminish when timing offset as well as channel coefficients and tap delays cannot be acquired.
Many UWB synchronizers rely on training, and some assume absence of inter-frame interference (IFI) and ISI, or, sampling rates as high as several GHz. Recently developed data aided and non-data aided algorithms for UWB receivers acquire timing via dirty-templates (TDT) formed from received noisy waveforms to cope with unknown channels inducing IFI but not ISI. These non-data aided TDT schemes require long data records and are available only for single-user links. In multi-access scenarios, the performance of such UWB receivers degrades significantly in the presence of ISI and MUI, even with data aided TDT.
Besides multi-access UWB links envisioned for wireless indoor pico-nets and potentially for low-power wireless sensor nets (WSN) outdoors, MUI constitutes a major performance-limiting factor when many asynchronous NB or WB communicators are to be synchronized, for example, at the base-station of a cellular code division multiple access (CDMA) system. Many blind CDMA approaches are subspace-based and do not ensure identifiability of multipath channels and timing offsets in the presence of ISI and MUI. Moreover, data aided as well as blind synchronizers for WB-CDMA over ISI channels are considerably complex because the synchronizers must estimate each users' channels and timing offsets, while typically assuming knowledge of the underlying symbol periodic or long spreading codes. However, such an assumption, i.e., knowledge of spreading codes, may not be satisfied by several multi-access ad hoc protocols.
Thus, synchronization is a performance-critical factor in communication systems from classical NB, WB, and emerging UWB point-to-point links to cooperative or ad hoc networking, where access must deal with MUI and possibly severe ISI.